Automated scalable contextual data collection and extraction system

    公开(公告)号:US10706063B2

    公开(公告)日:2020-07-07

    申请号:US15905041

    申请日:2018-02-26

    申请人: QOMPLX, Inc.

    摘要: A system for contextual data collection and extraction is provided, comprising an extraction engine configured to receive context from a user for desired information to extract, connect to a data source providing a richly formatted dataset, retrieve the richly formatted dataset, process the richly formatted dataset and extract information from a plurality of linguistic modalities within the richly formatted, and transform the extracted data into a extracted dataset; and a knowledge base construction service configured to retrieve the extracted dataset, create a knowledge base for storing the extracted dataset, and store the knowledge base in a data store.

    Quantification for investment vehicle management employing an advanced decision platform

    公开(公告)号:US10402906B2

    公开(公告)日:2019-09-03

    申请号:US15376657

    申请日:2016-12-13

    IPC分类号: G06Q40/06 G06Q40/04

    摘要: A system for investment vehicle quantification employing an advanced decision platform comprises a data retrieval module configured to retrieve investment related data. A predictive analytics module performs predictive analytics on investment data using investment specific and machine learning functions. A predictive simulation module performs predictive simulation functions on the investment data. An indexed global tile module retrieves geospatial and map overlay data, and serves as an interface for geospatial data requests. An interactive display module displays the results of predictive analytics and predictive simulation and both real world and simulated geospatial data.

    NETWORK ACTION CLASSIFICATION AND ANALYSIS USING WIDELY DISTRIBUTED HONEYPOT SENSOR NODES

    公开(公告)号:US20230370439A1

    公开(公告)日:2023-11-16

    申请号:US18361835

    申请日:2023-07-29

    申请人: QOMPLX, Inc.

    IPC分类号: H04L9/40 H04L9/32

    摘要: A system and methods for network action classification and analysis using widely distributed lightweight honeypot sensor nodes, comprising a plurality of network traffic sensors each configured to monitor visible network traffic, analyze monitored traffic to identify patterns, communicate with other network sensors to correlate their respective traffic data, and produce a threat landscape based on the correlated traffic data. The system and method may comprise an emulation engine configured to simulate limited services or functionalities, emulating vulnerabilities or weak points in systems. Emulation engine may comprise one or more modules configured to provide use-case specific emulation capabilities. Emulation engine may receive network traffic data from network sensors, route the network traffic to an appropriate simulated destination service associated with the network traffic, and monitor the interactions between an attacker and the simulated destination. Logged interactions may be used as an input to generate the threat landscape.

    Detecting and mitigating golden ticket attacks within a domain

    公开(公告)号:US11799900B2

    公开(公告)日:2023-10-24

    申请号:US17973520

    申请日:2022-10-25

    申请人: QOMPLX, Inc.

    IPC分类号: H04L9/40 G06F16/2458

    摘要: A system and methods for mitigating golden ticket attacks within a domain is provided, comprising an authentication object inspector configured to observe a new authentication object generated by an identity provider, and retrieve the new authentication object; and a hashing engine configured to retrieve the new authentication object from the authentication object inspector, calculate a cryptographic hash for the new authentication object, and store the cryptographic hash for the new authentication object in a data store; wherein subsequent access requests accompanied by authentication objects are validated by comparing hashes for each authentication object to previous generated hashes.

    SYSTEM AND METHOD FOR SELF-ADJUSTING CYBERSECURITY ANALYSIS AND SCORE GENERATION

    公开(公告)号:US20230300174A1

    公开(公告)日:2023-09-21

    申请号:US18299677

    申请日:2023-04-12

    申请人: QOMPLX, Inc.

    摘要: A system and method for self-adjusting cybersecurity analysis and score generation, wherein a reconnaissance engine gathers data about a client's computer network from the client, from devices and systems on the client's network, and from the Internet regarding various aspects of cybersecurity. Each of these aspects is evaluated independently, weighted, and cross-referenced to generate a cybersecurity score by aggregating individual vulnerability and risk factors together to provide a comprehensive characterization of cybersecurity risk using a transparent and traceable methodology. The scoring system itself can be used as a state machine with the cybersecurity score acting as a feedback mechanism, in which a cybersecurity score can be set at a level appropriate for a given organization, and data from clients or groups of clients with more extensive reporting can be used to supplement data for clients or groups of clients with less extensive reporting to enhance cybersecurity analysis and scoring.

    POLICY - AWARE VULNERABILITY MAPPING AND ATTACK PLANNING

    公开(公告)号:US20230208882A1

    公开(公告)日:2023-06-29

    申请号:US18069206

    申请日:2022-12-20

    申请人: QOMPLX, Inc.

    摘要: A system for continuous contextual policy-aware vulnerability mapping, security posture determination and attack planning and simulation, comprising an indexing service configured to create a dataset by processing and indexing source code of a project by a developer, perform a code audit on the indexed source code, store results from the code audit in the dataset, gather additional information relating to the provided project as intended and as operated, store the additional information in the dataset, and store the dataset into memory; and a monitoring service configured to continuously monitor the project for source code and operational changes and performance and make changes to the dataset as needed.